getMyPizza.py

def getMyPizza(ingredients):
    # load the dataset and clean the text
    pizza_df = pd.read_csv("PizzaIngredients.csv",na_values=['?'," ",""])
    pizza_df.Ingredients.replace(to_replace="[|]",value=" ",inplace=True,regex=True)
    myRow = ['MyPizza']  #converting ingredients column to list
    myRow.append(ingredients) 
    pizza_df.loc[len(pizza_df)] = myRow

    cv=CountVectorizer()
    cv_matrix=cv.fit_transform(pizza_df['Ingredients']) #gives the matrix of n*n with count of words matched
    cs=cosine_similarity(cv_matrix) #gives cosine similarity

    table=pd.DataFrame(index=pizza_df.PizzaName,columns=pizza_df.PizzaName,data=cs)
    table=table.drop(['MyPizza'],axis=1)
    if str(max(table.loc["MyPizza"])) != '0.0':
        return table.idxmax(axis=1)['MyPizza']
    else:
        return 0